Selective local transient improvement and peaking for video sharpness enhancement

ABSTRACT

A method of selectively sharpening an image may include, for at least some pixels in the image, determining a frequency content associated with a pixel value in the image. The pixel may be linearly sharpened if the frequency content exceeds a threshold. The pixel may be non-linearly sharpened if the frequency content does not exceed the threshold. In some implementations, the non-linear sharpening may include wavelet decomposition of the image and enhancement of decomposed components.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation-in-part of application Ser.No. 11/157,335, filed Jun. 20, 2005, (Docket No. P21783), the content ofwhich is hereby incorporated by reference, and is also acontinuation-in-part of application Ser. No. 11/184,688, filed Jul. 19,2005, (Docket No. P21764), the content of which is hereby incorporatedby reference.

BACKGROUND

Implementations of the claimed invention generally may relate to schemesfor enhancing video information and, more particularly, to such schemesthat alter the sharpness of the video information.

Video information may be transmitted via a medium in time and/or spacefor viewing at a separate time and/or location. In some cases, themedium may be a transmission medium, such as carrier waves (e.g.,terrestrial and/or cable-carried) or protocol-based data networks. Insome cases, the medium may be a storage medium (e.g., tape, hard disk,digital video disc (DVD), etc.) that may store the video informationprior to its display. Typically, the video data may be encoded into oneof a number of formats before transmission. Some encoding formats mayinclude, but are not limited to, MPEG-1, MPEG-2, MPEG-4, Advanced VideoCoding (AVC) (e.g., MPEG-4, part 10 and ITU-T Recommendation H.264),Windows Media Video 9 (WMV-9), and/or SMPTE's VC-1.

Such encoding of video information may remove (e.g., by quantizing,etc.) some higher-frequency content in the original video information.The decoded information may appear smoothed and/or somewhat fuzzy whendisplayed. This phenomenon may not be unique to encoded video data, butmay also be present in, for example, transmitted analog video due toimpediments in the transmission path. Thus, it may be desirable toincrease the sharpness of received and/or decoded video data to improveits perceived picture quality.

To further introduce the concept of sharpening video, a one-dimensionalexample will be discussed with regard to FIGS. 1A and 1B. An image in avideo sequence may include, for example, luma and chroma signals (e.g.,Y, U, and V) sampled in both the horizontal and vertical directions.When the image is roughly uniform in a certain area, the sample valuesmay be substantially the same. When an edge (e.g. a horizontal edge)exists in the image, however, the sample values in the horizontaldirection may undergo an abrupt change in value. FIG. 1A illustrates aone-dimensional plot 110 of luma values that change somewhat abruptlyover a number of pixels.

To sharpen the video signal, overshoots/undershoots may be generated inthe signal (e.g., Y, U or V) by adding the second derivative (e.g.,d²Y/dx²) of plot 110 to itself. FIG. 1B illustrates a plot 120 that hasbeen so sharpened by the addition of undershoot 130 and overshoot 140.Adding overshoot/undershoot 140/130 may boost perceived, higherfrequency components. Because plot 120 may have steeper edges than plot110, its transition may be perceived as visually sharper than that ofunsharpened plot 110.

Some schemes for increasing the sharpness of video information, however,may also increase noise within the video information to unacceptablelevels.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate one or more implementationsconsistent with the principles of the invention and, together with thedescription, explain such implementations. The drawings are notnecessarily to scale, the emphasis instead being placed uponillustrating the principles of the invention. In the drawings,

FIGS. 1A and 1B conceptually illustrate sharpening a video signal;

FIG. 2 illustrates a portion of a video display system;

FIG. 3 illustrates an exemplary linear sharpener in the system of FIG.2;

FIG. 4 conceptually illustrates an example convolution kernel;

FIG. 5 illustrates an exemplary gain profile of an amplifier in thelinear sharpener of FIG. 3;

FIG. 6 illustrates an exemplary non-linear sharpener in the system ofFIG. 2;

FIG. 7 illustrates an exemplary first order decomposition by thesharpener of FIG. 6; and

FIG. 8 illustrates an exemplary process of selectively changing thesharpness of video data.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.The same reference numbers may be used in different drawings to identifythe same or similar elements. In the following description, for purposesof explanation and not limitation, specific details are set forth suchas particular structures, architectures, interfaces, techniques, etc. inorder to provide a thorough understanding of the various aspects of theclaimed invention. However, it will be apparent to those skilled in theart having the benefit of the present disclosure that the variousaspects of the invention claimed may be practiced in other examples thatdepart from these specific details. In certain instances, descriptionsof well known devices, circuits, and methods are omitted so as not toobscure the description of the present invention with unnecessarydetail.

FIG. 2 illustrates a portion of a video display system 200. System 200may receive video information from any suitable medium, including butnot limited to various transmission and/or storage media. Althoughillustrated as separate functional elements for ease of explanation, anyor all of the elements of system 200 may be co-located and/orimplemented by a common group of gates and/or transistors. Further,system 200 may be implemented via software, firmware, hardware, or anysuitable combination thereof.

In various implementations, system 200 may include, or be part of, oneor more of a processing system, a processing sub-system, a processor, acomputer, a device, an encoder, a decoder, a coder/decoder (CODEC), afiltering device (e.g., graphic scaling device, deblocking filteringdevice), a transformation device, an entertainment system, a display, orany other processing architecture. The implementations are not limitedin this context.

The portion of display system 200 shown in FIG. 2 may include a linearsharpener 210, a non-linear sharpener 220, a selector 230, and a displaybuffer 240. The video data input to system 200 may have been decodedfrom any of a number of encoding schemes that may include, but are notlimited to, MPEG-1, MPEG-2, MPEG-4, Advanced Video Coding (AVC) (e.g.,MPEG-4, part 10 and ITU-T Recommendation H.264), Windows Media Video 9(WMV-9), and/or SMP E's VC-1.

Linear sharpener 210 may function to selectively sharpen a stream ofvideo images. In some implementations, linear sharpener 210 maydifferently sharpen certain portions of a picture in the video streambased on their amplitudes and/or their neighboring pixels.

FIG. 3 illustrates an implementation of linear sharpener 210. Linearsharpener 210 may include a convolver 310, an amplifier 320, and acombiner 330. Although illustrated as being connected in a certainmanner for ease of illustration, linear sharpener 210 in FIG. 3 may beconnected in other configurations. For example, in some implementations,combiner 330 may be located before amplifier 320, instead of after asshown. Other variations are both possible and contemplated.

Convolver 310 may be arranged to sharpen a pixel (e.g., Y, U, and/or Vcomponent) of video data by adding content to the pixel. Convolver 310may convolve a two-dimensional (2D) Laplacian kernel with a number ofpixels surrounding the pixel in question to obtain a derivative value.Such derivative value, the output of convolver 310, may be referred toas a sharpening value.

For example, in some implementations, convolver 310 may use a 5×5kernel, such as Laplacian convolution kernel 410 shown in FIG. 4.Convolver 310 may convolve kernel 410 with, for example, the 5×5 lumadata containing the pixel in question to obtain the 2D derivative of theluma signal. The output of convolver 310 may be, for example, a 7×7array as a result of convolution of the 5×5 luma (or chroma) data withthe 5×5 kernel. The sharpening value output by convolver 310 may be thecenter value of such resulting array that corresponds to the pixel inquestion.

Other variations than this specific example are contemplated. Forexample, a different-sized kernel may be used by convolver 310 thankernel 410. In some implementations, the same or different kernels maybe used for luma (e.g., Y) and chroma (e.g., U and/or V) video data. Insome implementations, only the luma data may be convolved, while passingthe chroma data unaltered.

Returning to FIG. 3, amplifier 320 may be arranged to selectivelyincrease the sharpening value from convolver 310 to produce an amplifiedvalue. In some implementations, amplifier 320 may apply a nonlinear gaincurve that depends on the input, sharpening values to produce amplifiedvalues. For example, in some implementations, amplifier 320 may notsupply (and/or apply) gain to those sharpening values that do not exceedaround 5% (or another relatively small threshold) of the overall dynamicrange of the pixel values that are input to convolver 310. Suchselective amplification by amplifier 320 may avoid amplifying noisebelow a certain signal level (e.g., preventing “coring” in a final,sharpened pixel value output by combiner 330). Similarly, in someimplementations, amplifier 320 also may not supply and/or apply gain tosharpening values that exceed a certain threshold. In this manner,amplifier 320 may also prevent clipping in the final, sharpened pixelvalue output by combiner 330.

FIG. 5 illustrates an exemplary gain profile 500 of amplifier 320. Insome implementations, there may exist a desired or preferred gainprofile 510, shown as a dashed line. In the implementation of FIG. 5,gain profile 500 may be a piecewise linear approximation of desiredprofile 510. Other implementations are possible and contemplated,however, such as a curvilinear approximation of desired profile 510(e.g., a quadratic or cubic function). In some implementations, desiredprofile 510 may be implemented exactly, such as via a look-up table.

Gain profile 500 may illustrate the gain (or gain scale factor) ofamplifier 320 versus the input signal (e.g., the sharpening value fromconvolver 310, which may be luminance and/or chrominance) Gain profile500 may be substantially zero up to a coring point 520, may generallyincrease between coring point 520 and an intermediate point 530, maygenerally decrease between intermediate point 520 and a clipping point540, and may be substantially zero beyond clipping point 540. A maximumvalue 550 of profile 500 may occur when the input value is atintermediate point 530.

In some implementations, (e.g., where a full scale value of may be 255,corresponding to 8 bits), coring point 520 may be about 40, andintermediate point 530 may be about 50. In some implementations,clipping point 540 may be a suitable value to prevent clipping in thefinal, sharpened pixel value output by combiner 330. In someimplementations, maximum value 550 may be set to 125, almost half of thefull scale value. Other values are possible, however. It should be notedthat the non-zero portions of gain profile 500 need not be symmetricalabout intermediate point 530.

Returning to FIG. 3, although amplifier 320 (and associated gain profilein FIG. 5) has been described as operating based on the sharpeningvalues output by convolver 310, in some implementations amplifier 320may operate based on the video data (e.g., pre-sharpened values) inputto convolver 310. In some implementations, amplifier 320 may operatebased on the combination of the pre-sharpened pixel data and thesharpening values output by convolver 310. Regardless of which dataamplifier 320 operates based upon, it may function to prevent coringand/or clipping in the sharpened pixel values output by combiner 330.

Combiner 330 may combine the amplified values from amplifier 320 withpixel values that were input to convolver 310 to output sharpened pixelvalues. In some implementations, combiner 330 may include an adder toadd an amplified value from amplifier 320 to a corresponding unsharpenedpixel value. In some implementations, combiner 330 may include otherlogic to arithmetically (e.g., subtracter, multiplier, etc.) and/orlogically (e.g., AND, XOR, etc.) combine an amplified values tocorresponding pixel values as appropriate.

Returning to FIG. 2, non-linear sharpener 220 may function toselectively sharpen a stream of video images. In some implementations,non-linear sharpener 220 may differently sharpen certain portions of apicture in the video stream based on a frequency-based, non-lineartransformation of the images.

FIG. 6 illustrates an implementation of non-linear sharpener 220.Non-linear sharpener 220 may include a wavelet decomposition module 610,a horizontal edge enhancement module 660, a vertical edge enhancementmodule, a diagonal edge enhancement module 680, and a reconstructionmodule 690.

Wavelet decomposition module 610 may be arranged to receive an inputimage 620. Input image 620 may include, for example, a picture in avideo sequence including signals (e.g., Y, U, and V) sampled in both thehorizontal and vertical directions. The implementations are not limitedin this context.

In various implementations, the wavelet decomposition module 610 may bearranged to perform wavelet decomposition. The wavelet decomposition mayinclude two-dimensional orthogonal wavelet decomposition, for example.The wavelet decomposition may automatically detect edge information inany general direction in the signal components (e.g., YUV or RGB). Itcan be appreciated that various wavelet decompositions may be used. Theimplementations are not limited in this context.

In various implementations, wavelet decomposition may includedetermining the location of the edges as well as making the edgessteeper by modifying the constituent frequency components. The waveletdecomposition may include performing wavelet analysis for edge detectionand/or transient processes. The edge information may be decomposed via awavelet filter bank, for example, and the frequency-amplitudedistribution for the edges may be adaptively changed. The wavelets mayinclude time aspects and scale or space aspects, which enable analysisin both time and space for any physical phenomenon. Wavelet analysis mayinclude a windowing technique with variable-sized regions. Waveletanalysis may allow the use of long time intervals where more preciselow-frequency information is desired, and the use of shorter regionswhere high-frequency information is desired. The implementations are notlimited in this context.

The wavelet decomposition may include employing a wavelet transform. Invarious implementations, the wavelet transform may include atwo-dimensional discrete wavelet transform (2D-DWT) such as a Debauchieswavelet transform, for example. In various implementations, the wavelettransform may use dyadic scales and positions following a geometricsequence of ratio two in order to reduce the amount of waveletcoefficient calculations. The dyadic wavelet transform improvesefficiency and generally is just as accurate. The implementations arenot limited in this context.

In various implementations, the wavelet decomposition may includeperforming multiple levels of decomposition. In one implementation, forexample, the wavelet decomposition may include three levels ofdecomposition. The 2D-DWT, for example, may decompose an image into alow-detail component and three higher-detail components (e.g., includinghigher-frequency information) in a horizontal direction, in a verticaldirection, and in a diagonal direction. Those familiar with DWT mayrecognize that after a first-level decomposition, a resulting low-detailcomponent may be successively decomposed in second, third, etc. leveldecompositions. The implementations are not limited in this context.

Wavelet decomposition module 610 may arranged to perform waveletdecomposition on original image 620. In various implementations, thewavelet decomposition module 610 may perform a three-level,two-dimensional wavelet decomposition (e.g., 2D-DWT) to generate a firstlevel decomposition 630, a second level decomposition 640, and a thirdlevel decomposition 650. The implementations are not limited in thiscontext.

Horizontal edge enhancement module 660, vertical edge enhancementmodule, and diagonal edge enhancement module 680 may be arranged tochange the decomposition output (e.g., 2D-DWT output). In variousimplementations, horizontal, vertical and diagonal enhancement may beapplied only to the detail components (e.g., higher frequency) of thewavelet decomposition, while the approximation component (e.g., lowerfrequency) of every level of wavelet decomposition may be passed toreconstruction module 690 without any enhancement. Such may ensure thesharpness enhancement method does not respond to the low frequencycomponents in the image, but rather to the mid and high frequencycomponents. The implementations are not limited in this context.

In various implementations, the horizontal edge enhancement module 660,the vertical edge enhancement module, and the diagonal edge enhancementmodule 680 may be arranged to pad higher frequency components with morecomponents, which fit the decomposed components. The differentdecomposition levels may be treated differently (soft threshold), basedon the relative amount of energy in every decomposition level. Invarious implementations, the 2D-DWT decomposition may be modified byboosting the high frequency components in the horizontal, vertical anddiagonal directions at the first level with a factor t1, at the secondlevel with a factor t2, and at the third level with a factor t3, wheret1>t2>t3. The implementations are not limited in this context.

Horizontal edge enhancement module 660 may boost the high frequencycomponents from the first level decomposition 630 in the horizontaldirection by a first enhancement factor t_(h) 1. The horizontal edgeenhancement module 660 may boost the high frequency components from thesecond level decomposition 640 in the horizontal direction by a secondenhancement factor t_(h) 2. The horizontal edge enhancement module 660may boost the high frequency components from the third leveldecomposition 650 in the horizontal direction by a third enhancementfactor t_(h) 3 (t_(h) 1>t_(h) 2>t_(h) 3). The implementations are notlimited in this context.

Vertical edge enhancement module 670 may boost the high frequencycomponents from the first level decomposition 630 in the verticaldirection by a first enhancement factor t_(v) 1. The vertical edgeenhancement module 670 may boost the high frequency components from thesecond level decomposition 640 in the vertical direction by a secondenhancement factor t_(v) 2. The vertical edge enhancement module 670 mayboost the high frequency components from the third level decomposition650 in the vertical direction by a third enhancement factor t_(v) 3(t_(v) 1>t_(v) 2>t_(v) 3). The implementations are not limited in thiscontext.

Diagonal edge enhancement module 680 may boost the high frequencycomponents from the first level decomposition 630 in the diagonaldirection by a first enhancement factor t_(d) 1. The diagonal edgeenhancement module 680 may boost the high frequency components from thesecond level decomposition 640 in the diagonal direction by a secondenhancement factor t_(d) 2. The diagonal edge enhancement module 680 mayboost the high frequency components from the third level decomposition650 in the diagonal direction by a third enhancement factor t_(d) 3(t_(d) 1>t_(d) 2>t_(d) 3). The implementations are not limited in thiscontext.

Reconstruction module 690 may be arranged to perform reconstructionusing the modified decomposition levels. In various implementations, thereconstruction module 690 may receive the enhanced horizontal, verticaland diagonal detail component of the wavelet decomposition fromhorizontal edge enhancement module 660, vertical edge enhancement module670, and diagonal edge enhancement module 680. Reconstruction module 690may receive the approximation component (low frequency) of every levelof wavelet decomposition without enhancement from wavelet decompositionmodule 610. In various implementations, the reconstruction module 690may use the modified frequency components of the luma and/or chorma (Yand/or UV) signals and perform inverse transformation to obtain everyimage back from the wavelet transforms. The implementations are notlimited in this context.

In some cases, if the edge information is weak, weak real signals may beconfused with noise. In various implementations, a local noisemeasurement technique may be used to adaptively decide on the localthreshold for noise presence to remedy this situation. The local noisemeasurement technique may adaptively determine a coring value based onthe picture contents. The coring value may be set to a very lowpercentage of the input signal (YU or V), depending on the picturecharacteristics. In various implementations, the coring value may be setto 2-4% so that almost 96% of the original values are excluded (assuminga valid Gaussian assumption) to hypothesize the coring threshold in animage. The coring value may be used locally at every decomposition levelto measure the level of noise and to give a localized measure both inthe time domain (the image itself) and in the frequency domain (everydecomposition level). The implementations are not limited in thiscontext.

Returning to FIG. 2, selector 230 may select between the outputs oflinear sharpener 210 and non-linear sharpener 220 to output to displaybuffer 240 based on information from non-linear sharpener 220 (shown asa dotted line in FIG. 2). In some implementations, selector 230 maydefault to outputting the sharpened video information from non-linearsharpener 220, unless there are particularly sharp edges in the image620. In the presence of such sharp edges, selector may output thesharpened video information from linear sharpener 210 instead.

In some implementations, selector 230 may use the higher-frequencyinformation in first-level decomposition 630 to determine the presenceor absence of sharp edges. Selector 230 may determine areas ofhigh-density spatial frequencies from any one, two, or all threehigher-detail components of decomposition 630 (e.g., in the horizontaldirection, in the vertical direction, and/or in the diagonal direction).Various schemes and criteria for determining areas of high spatialfrequencies are possible. For example, selector 230 may make suchdetermination on a pixel-by-pixel (or groups of pixels) basis bycomparing the higher-detail components of decomposition 630 with athreshold. In some implementations, selector 230 may make suchdetermination for a certain number of pixels (or blocks) adjacent to apixel for which such a threshold is exceeded. In some implementations,selector 230 may determine areas of high-density via a certain number ofthreshold-exceeding values within a certain area (e.g., block,macroblock, etc.).

Purely for the purposes of illustration, FIG. 7 shows an exemplaryfirst-level, 2D wavelet decomposition 630 including a low-detailcomponent 710 and three high-detail components (e.g., includinghigh-frequency information) in a horizontal direction (i.e., horizontalcomponent 720), in a vertical direction (i.e., vertical component 730),and in a diagonal direction (i.e., diagonal component 740). Selector 230may select the output of linear sharpener 210 for certain pixelscorresponding to the circled area(s) of component(s) 720, 730, and/or740 (e.g., regions high spatial density), and may select the output ofnon-linear sharpener 220 for all other pixels (e.g., regions low spatialdensity). Although the claimed invention may be performed usingcomponents from a first-level wavelet decomposition 630, it should notbe limited thereto, as it may also be performed with higher-levelwavelet decompositions and/or other types of transformations to extract,for example, high-frequency components 720-740 or similar high-frequencyinformation.

Returning to FIG. 2, display buffer 240 may receive video data fromselector 230, and may temporarily store at least some of such data priorto its output to a display device (not shown). In addition to abuffering (e.g., storage) function, display buffer 240 may perform otherdisplay-related tasks, such as synchronizing its output signal to atiming or sync signal to facilitate display. Other functionality that istypically found in display buffers may also be present in display buffer240.

FIG. 8 illustrates an example process 800 of selectively changing thesharpness of video data. Although FIG. 8 may be described with regard tosystem 200 described in FIGS. 2-7 for ease and clarity of explanation,it should be understood that process 800 may be performed by otherhardware and/or software implementations.

Processing may begin by selector 230 determining a frequency contentassociated with a pixel, or a group of pixels [act 810]. Thisdetermination may be made, as previously described, based on frequencycontent in a first-order wavelet decomposition 630, in any or all of thehorizontal, vertical and/or diagonal directions.

If the frequency content of the pixel, or group of pixels, is determinedto be high [act 820], selector 230 may output a sharpened pixel valuefrom linear sharpener 210 for this pixel or group of pixels [act 830].In this manner, system 200 avoids introducing noise and/or otherundesirable effects by increasing to a greater degree (e.g.,non-linearly) the already high frequency content. Instead, these areasof high frequency content may be sharpened to a lesser degree (e.g., afirst order or lower sharpening, which may be generally referred to as“linear”).

If the frequency content of the pixel, or group of pixels, is notdetermined to be high [act 820], selector 230 may output a sharpenedpixel value from non-linear sharpener 220 for this pixel or group ofpixels [act 840]. In this manner, system 200 may sharpen these areas ofrelatively low frequency content to a greater degree (e.g., a secondorder or higher sharpening, which may be generally referred to as“non-linear”). Because an image may typically contain a greaterpercentage of low-frequency content (e.g., 80%, 90%, 95%, etc.), thegreater, non-linear sharpening in act 840 may be considered the“default” case, and act 830 may be performed in the generally smallernumber of cases where sharp edges (e.g., high frequency content) arepresent.

The foregoing description of one or more implementations providesillustration and description, but is not intended to be exhaustive or tolimit the scope of the invention to the precise form disclosed.Modifications and variations are possible in light of the aboveteachings or may be acquired from practice of various implementations ofthe invention.

For example, although the scheme described herein may be performed on apixel-by-pixel basis, it may also be performed for aggregations orgroups of pixels in an image. Also as used herein, the terms “linear”and “non-linear” should not be interpreted strictly. Rather, “linear” isused herein as convenient shorthand for first-order or lower (i.e.,0^(th) order) sharpening. For example, gain profile 500 includes zeroand piecewise linear portions, but it may be considered “linear” in thatit contains first-order or lower content. Similarly, “non-linear” asused herein need not necessarily exclude first-order content. Rather,the term “non-linear” as used herein may denote the presence ofsecond-order (e.g., quadratic) or higher sharpening.

Moreover, the scheme described herein should not be limited to thespecific implementations disclosed (e.g., selective amplification andwavelet-based), but rather may apply to any technique that sharpens in asuper-linear manner, except where high spatial frequencies are present.The claimed invention is intended to encompass any such technique thatsharpens such higher-frequency content less, and possibly with adifferent technique.

Further, at least some of the acts in FIG. 7 may be implemented asinstructions, or groups of instructions, implemented in amachine-readable medium.

No element, act, or instruction used in the description of the presentapplication should be construed as critical or essential to theinvention unless explicitly described as such. Also, as used herein, thearticle “a” is intended to include one or more items. Variations andmodifications may be made to the above-described implementation(s) ofthe claimed invention without departing substantially from the spiritand principles of the invention. All such modifications and variationsare intended to be included herein within the scope of this disclosureand protected by the following claims.

1. A method, comprising: determining a frequency content associated witha pixel value in an image; linearly sharpening the pixel if thefrequency content exceeds a threshold; and non-linearly sharpening thepixel if the frequency content does not exceed the threshold.
 2. Themethod of claim 1, wherein the determining includes: decomposing theimage using wavelets into a first level wavelet decomposition.
 3. Themethod of claim 2, wherein the frequency content includes a horizontalcomponent in the first level wavelet decomposition, a vertical componentin the first level wavelet decomposition, or a diagonal component in thefirst level wavelet decomposition.
 4. The method of claim 1, wherein thelinearly sharpening includes: generating a sharpening value for thepixel value, amplifying the sharpening value in a piecewise linearmanner to produce an amplified value, and combining the pixel value andthe amplified value.
 5. The method of claim 4, wherein the generatingincludes: convolving the pixel value and a number of surrounding pixelswith a kernel to produce the sharpening value.
 6. The method of claim 1,wherein the non-linearly sharpening includes: performing a waveletdecomposition of the image to produce an output, and enhancing highfrequency components of the output of the wavelet decomposition.
 7. Themethod of claim 6, wherein the non-linearly sharpening further includes:reconstructing the image based on the enhanced high frequency componentsof the output of the wavelet decomposition.
 8. A system, comprising: alinear sharpener to selectively sharpen a pixel of an image and tooutput a linearly sharpened value for the pixel; a non-linear sharpenerto selectively sharpen the pixel and to output a non-linearly sharpenedvalue for the pixel; and a selector to choose one of the linearlysharpened value and the non-linearly sharpened value as an output valuebased on frequency content associated with the pixel.
 9. The system ofclaim 8, wherein the frequency content is obtained from the non-linearsharpener.
 10. The system of claim 8, wherein the linear sharpenerincludes: a sharpening portion to sharpen the pixel and output asharpening value, an amplifier to apply a gain, that changes a functionof sharpening value, to the sharpening value to produce an alteredvalue, and a combiner to combine the altered value and the pixel and tooutput the linearly sharpened value.
 11. The system of claim 10, whereinthe sharpening portion includes: a convolver to convolve the pixel and anumber of surrounding pixels with a similarly sized kernel.
 12. Thesystem of claim 8, wherein the non-linear sharpener includes: a waveletdecomposition module to perform wavelet decomposition of the image todetect and modify edge information, and an edge enhancement module toenhance wavelet decomposition output from the wavelet decompositionmodule.
 13. The system of claim 12, wherein the non-linear sharpenerfurther includes: a reconstruction module to perform imagereconstruction based on outputs from the wavelet decomposition moduleand the edge enhancement module.
 14. The system of claim 8, wherein theselector is arranged to choose the linearly sharpened value as theoutput value when the frequency content associated with the pixelexceeds a threshold, and wherein the selector is arranged to choose thenon-linearly sharpened value as the output value when the frequencycontent associated with the pixel does not exceed the threshold.
 15. Thesystem of claim 8, further comprising: a display buffer to store theoutput value from the selector.
 16. A method, comprising: sharpening apixel in an image by a first amount using a first sharpening techniqueto produce a first sharpened value; sharpening the pixel in the image bya second amount that is less than the first amount using a secondsharpening technique to produce a second sharpened value; selecting thesecond sharpened value if a spatial frequency associated with the pixelis high; and selecting the first sharpened value if the spatialfrequency associated with the pixel is not high.
 17. The method of claim16, wherein the first sharpening technique includes waveletdecomposition of the image, enhancement of decomposed components, andreconstruction of the image.
 18. The method of claim 16, wherein thesecond sharpening technique includes applying a piecewise linear gainfunction to a sharpening value for the pixel.
 19. The method of claim17, wherein the spatial frequency associated with the pixel is obtainedfrom the decomposed components.